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    Mads EgmoseNew Participant

    Fin AI: draft email replies for human reviewSubmitted

    ProblemFin handles chat well — short turns, fast iteration, low downside if a reply needs a follow-up. Email is a different beast. Threads are longer, context spans days or weeks, and the stakes are higher: customers expect a considered, accurate response, and a wrong reply is much harder to walk back than in a live chat.That makes full autonomy a poor fit for most email conversations. But it doesn't mean Fin can't help. Right now, the gap between "Fin resolves it autonomously" and "agent writes from scratch" is too wide for email — there's nothing in between.ProposalWhen a new email arrives, Fin generates a draft reply using:- The full thread context- Connected knowledge sources (help center, macros, past resolved threads)- Brand voice and tone settings already configured for FinThe draft sits in the conversation ready for an agent to review, edit, or send. A confidence indicator and visible source citations would let agents verify in seconds rather than re-researching the answer.Why this is valuable- Cuts response time without giving up the human-in-the-loop check that email genuinely needs.- Captures Fin's value on conversations that today are 100% manual.- Creates a feedback loop: agent edits become signal for improving future drafts, and eventually for moving simpler email categories toward autonomous resolution.Use caseWe run a marketplace where most supplier-side conversations happen over email. They're rarely fully automatable, but most of what we write is a variation of something we've written before. A Fin draft would save the majority of the writing time per reply while keeping us in control of what actually ships.

    Roy
    Top Expert ✨
    RoyTop Expert ✨

    🚀 Feature Request: "Direct API Mapping" for FinSubmitted

    The Problem: Currently, setting up Fin Data Connectors is a high-friction process. For every action we want Fin to take, we have to manually: Create a new Connector. Define the endpoint. Manually map and explain each data attribute so Fin understands it.  This significantly increases the "Time to Value" for Fin. If I have a complex B2B API with 50 endpoints, it takes days to set up, rather than minutes. ⏳ The Solution: Introduce a "Bulk API Mapping" feature. Instead of manual entry, allow us to provide a URL to our API Documentation (or upload an OpenAPI/Swagger JSON/YAML file) and the Global Authorization headers.How it would work: Doc Ingestion: Fin "reads" the documentation and automatically maps the available endpoints. Semantic Understanding: Since modern API docs are well-designed, Fin can use its native LLM capabilities to understand what each endpoint does without us writing a manual "explanation" for every single one. Global Auth: Set authorization once at the root level rather than per-connector. Selective Enabling: A simple toggle list where we can "Turn On" specific endpoints for Fin to use as Tools.  Why this is a game-changer: ⚡️ Drastically Reduce Start Time: We could go from "Zero to Integrated" in minutes, not days. 📈 Scale Automation: It encourages teams to give Fin more "powers" because the cost of adding a new capability is nearly zero. 🛠 Improved Accuracy: Professional API documentation is often clearer than a human's manual summary, leading to fewer hallucinations during tool calls.  Let’s move Fin from a "manual data connector" model to a "plug-and-play architect" model! 🇬🇧💪#IntercomFin #ProductFeedback #FeatureRequest